Decision Making Under Uncertainty

Energy and Power

  • Claude Greengard
  • Andrzej Ruszczynski

Part of the The IMA Volumes in Mathematics and its Applications book series (IMA, volume 128)

Table of contents

  1. Front Matter
    Pages i-ix
  2. Robert Burridge, Benoît Couët, François Auzerais, Vassilios Vassiliadis
    Pages 17-37
  3. Nicole Gröwe-Kuska, Krzysztof C. Kiwiel, Matthias P. Nowak, Werner Römisch, Isabel Wegner
    Pages 39-70
  4. Stein-Erik Fleten, Stein W. Wallace, William T. Ziemba
    Pages 71-93
  5. Edward J. Anderson, Andrew B. Philpott
    Pages 115-133
  6. Frederic H. Murphy, Suvrajeet Sen
    Pages 135-151
  7. Back Matter
    Pages 153-163

About these proceedings

Introduction

In the ideal world, major decisions would be made based on complete and reliable information available to the decision maker. We live in a world of uncertainties, and decisions must be made from information which may be incomplete and may contain uncertainty. The key mathematical question addressed in this volume is "how to make decision in the presence of quantifiable uncertainty." The volume contains articles on model problems of decision making process in the energy and power industry when the available information is noisy and/or incomplete. The major tools used in studying these problems are mathematical modeling and optimization techniques; especially stochastic optimization. These articles are meant to provide an insight into this rapidly developing field, which lies in the intersection of applied statistics, probability, operations research, and economic theory. It is hoped that the present volume will provide entry to newcomers into the field, and stimulation for further research.

Keywords

Stochastic Optimization Stochastic Programming electricity electricity markets mathematical modeling model modeling operations research optimization programming statistics

Editors and affiliations

  • Claude Greengard
    • 1
  • Andrzej Ruszczynski
    • 2
  1. 1.IBM Watson Research CenterHawthorneUSA
  2. 2.Department of Management Science and Information SystemsRutgers UniversityPiscatawayUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4684-9256-9
  • Copyright Information Springer-Verlag New York 2002
  • Publisher Name Springer, New York, NY
  • eBook Packages Springer Book Archive
  • Print ISBN 978-1-4419-3014-9
  • Online ISBN 978-1-4684-9256-9
  • Series Print ISSN 0940-6573
  • About this book